Anonymization Privacy Security and Preserving Similarity Joins for Secured Data
Ms. S. Deepa · International Journal for Research in Applied Science and Engineering Technology · 2018
This project proposed a paper approach to share accommodating -specific lengthwise data that offers booming confidentiality guarantees, while preserving data utility for many biomedical investigations. The proposal summation temporal and rectifying information using heuristics excited from continuance alignment and gathering methods. The thesis exposes that the proposed approach can achieve anonymized information that allow powerfull biomedical analysis using many patient disciple imitative from the EMR system. In this thesis, aside from the above work, two obligation clarify this issues on suppression-based and generalization-based k-anonymous and secrete databases are approached. The protocols rely on renowned cryptographic presumption, and we provide theoretical analyses to proof their correctness and provisional results to exhibit their capability.